Arif Bayirli

• Member of the ATLAS Experiment based in Geneva, fully funded by CERN. • Lead developer for the project, improving electron identification performance of the detector using sequence-based machine learning methods with Recurrent Neural Networks. The tool that I am developing will be deployed in the C++ production environment and be used in the next phase of the LHC which will start in 2021.

Full-time official job in university for selected PhD students; tresponsible for teachinglaboratory courses and giving problem sessions and tutorials on physics courses as well as mentoring students.

Installed, configured and troubleshoot small-to-mid scale networks using Cisco routers, switches and firewalls.

Thesis topic: Machine Learning Methods applied to Jet Physics Relevant skills: Big scale data analysis using state-of-the-art deep learning models

Thesis Title: Chameleon Search in CAST Experiment at CERN, 2017 Relevant skills: Data analysis using numerical linear algebra tools such as Fast Fourier Transform

Concentration in Astrophysics Relevant skills: Data analysis with NASA Fermi satellite data using time series methods

Attended - Switched to Physics in my 3rd year